Has traveledinternationallyto attend thisconferenceHas presenteda paper onnaturallanguagegenerationCanrecommenda good AI ortech relatedpodcastIs optimisticabout thefuture ofhuman-AIcollaborationIs excitedabout thepotential ofLLMs ineducationIs interestedin the ethicalimplicationsof generativeAIHas used anLLM tosummarizeresearchpapersCan namethreedifferent LLMarchitecturesHascontributedto an open-source AIprojectHas used agenerative AImodel for anon-academicpurposeHas apreferred AIresearch toolthey canrecommendCan explain thedifferencebetween causaland maskedlanguagemodelsHas collaboratedon a researchpaper withsomeone from adifferent continentHas learneda newlanguage inthe last yearHassuccessfullydebugged acomplexLLMKnows atleast threeprogramminglanguagesIs familiarwith theconcept ofpromptengineeringHas used agenerative AImodel tocreate art ormusicHasexperiencewith fine-tuning a pre-trained LLMIs currentlyworking on aprojectinvolving cross-lingual transferlearningHasattended anICMLconferencebeforeHaspublishedresearch onmultilingualLLMsHasparticipated ina hackathonfocused on AIor LLMsHas experiencewith low-resourcelanguages inNLPHas traveledinternationallyto attend thisconferenceHas presenteda paper onnaturallanguagegenerationCanrecommenda good AI ortech relatedpodcastIs optimisticabout thefuture ofhuman-AIcollaborationIs excitedabout thepotential ofLLMs ineducationIs interestedin the ethicalimplicationsof generativeAIHas used anLLM tosummarizeresearchpapersCan namethreedifferent LLMarchitecturesHascontributedto an open-source AIprojectHas used agenerative AImodel for anon-academicpurposeHas apreferred AIresearch toolthey canrecommendCan explain thedifferencebetween causaland maskedlanguagemodelsHas collaboratedon a researchpaper withsomeone from adifferent continentHas learneda newlanguage inthe last yearHassuccessfullydebugged acomplexLLMKnows atleast threeprogramminglanguagesIs familiarwith theconcept ofpromptengineeringHas used agenerative AImodel tocreate art ormusicHasexperiencewith fine-tuning a pre-trained LLMIs currentlyworking on aprojectinvolving cross-lingual transferlearningHasattended anICMLconferencebeforeHaspublishedresearch onmultilingualLLMsHasparticipated ina hackathonfocused on AIor LLMsHas experiencewith low-resourcelanguages inNLP

Human BINGO: Navigating Generative AI and LLMs Across Languages - Call List

(Print) Use this randomly generated list as your call list when playing the game. There is no need to say the BINGO column name. Place some kind of mark (like an X, a checkmark, a dot, tally mark, etc) on each cell as you announce it, to keep track. You can also cut out each item, place them in a bag and pull words from the bag.


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  1. Has traveled internationally to attend this conference
  2. Has presented a paper on natural language generation
  3. Can recommend a good AI or tech related podcast
  4. Is optimistic about the future of human-AI collaboration
  5. Is excited about the potential of LLMs in education
  6. Is interested in the ethical implications of generative AI
  7. Has used an LLM to summarize research papers
  8. Can name three different LLM architectures
  9. Has contributed to an open-source AI project
  10. Has used a generative AI model for a non-academic purpose
  11. Has a preferred AI research tool they can recommend
  12. Can explain the difference between causal and masked language models
  13. Has collaborated on a research paper with someone from a different continent
  14. Has learned a new language in the last year
  15. Has successfully debugged a complex LLM
  16. Knows at least three programming languages
  17. Is familiar with the concept of prompt engineering
  18. Has used a generative AI model to create art or music
  19. Has experience with fine-tuning a pre-trained LLM
  20. Is currently working on a project involving cross-lingual transfer learning
  21. Has attended an ICML conference before
  22. Has published research on multilingual LLMs
  23. Has participated in a hackathon focused on AI or LLMs
  24. Has experience with low-resource languages in NLP